Consensus Based Overlapping Decentralized Estimator
Consensus Based Overlapping Decentralized Estimator
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DOI：
10.1109/acc.2007.4282751
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发表时间：
2007-07
期刊：
影响因子：
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通讯作者：
S. Stankovic;M. Stanković;D. Stipanović
中科院分区：
文献类型：
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作者：
S. Stankovic;M. Stanković;D. Stipanović
本文提出了一种新的状态估计算法，其形式是基于局部卡尔曼滤波器之间的协同作用和智能体之间的动态一致性策略的多智能体网络。它表明，它是可能的，在非常一般的条件下，关于本地资源和网络拓扑结构，通过适当选择的共识增益，以实现整个估计算法的渐近稳定。结果表明，一致性增益可以通过最小化总的均方估计误差来获得。一些例子说明所提出的方法的效率和适用性。
In this paper a new algorithm for state estimation is proposed in the form of a multi-agent network based on a synergy between local Kalman filters and a dynamic consensus strategy between the agents. It is shown that it is possible, under very general conditions concerning local resources and the network topology, to achieve asymptotic stability of the whole estimation algorithm by a proper choice of the consensus gains. It is demonstrated that the consensus gains can be obtained by minimizing the total mean-square estimation error. A number of examples illustrate efficiency and applicability of the proposed methodology.